Instructions to use tweettemposhift/hate-hate_balance_random3_seed2-bernice with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use tweettemposhift/hate-hate_balance_random3_seed2-bernice with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="tweettemposhift/hate-hate_balance_random3_seed2-bernice")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("tweettemposhift/hate-hate_balance_random3_seed2-bernice") model = AutoModelForSequenceClassification.from_pretrained("tweettemposhift/hate-hate_balance_random3_seed2-bernice", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from tweettemposhift/hate-hate_balance_random3_seed2-bernice: direct link, hf CLI and curl.
- Browser
- Download file 4.54 kB
-
https://huggingface.co/tweettemposhift/hate-hate_balance_random3_seed2-bernice/resolve/main/training_args.bin
- Command line
-
hf download hf://tweettemposhift/hate-hate_balance_random3_seed2-bernice/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/tweettemposhift/hate-hate_balance_random3_seed2-bernice/resolve/main/training_args.bin
4.54 kB
- Xet hash:
- 5d783b3e5a8910b269e0e2e94baba2894c1bcf3e0276dd6deb9b807e7fdd825d
- Size of remote file:
- 4.54 kB
- SHA256:
- 89d147f1b69b6401635a7b747d52cd887660b170c8fc9fb7c4363c499224066c
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.